Analyze Zika infected Glioblastoma data:

### Finding gene modules that make cells susceptible to Zika infection

title: “Finding gene modules that make cells susceptible to Zika infection”
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Load the required R libraries:

library(Seurat)
library(Matrix)
library(EnsDb.Hsapiens.v75)
library(rhdf5)
library(dplyr)

Here I 1.) load the data 2.) change the gene identifiers from ensemble ids to symbols 3.) construct a metadata matrix (with donor information, Zika exposure etc.) 4.) put the data and metadata into a Seurat object. 5.) load mitochondrial genes from a database for later use.

setwd('/home/jovyan/HB_ZIK/')
# glioblastoma_counts = read.delim('../data/ZikaGlioblastomas/tic-527/study5953-tic527-star-fc-genecounts.txt', row.names = 1)
# manifest = read.delim('../HB_ZIK/5953stdy_manifest_14517_170919_HB_ZIK_046_048_050_051.csv', sep = ',', skip = 8)
# manifest = manifest[manifest$SUPPLIER.SAMPLE.NAME != "",]
# glioblastoma_metadata = data.frame(matrix('', dim(glioblastoma_counts)[2],4))
# colnames(glioblastoma_metadata) = c('SampleName', 'Technology', 'ZikaExposure', 'Patient')
# glioblastoma_metadata[,1] = unlist(lapply(colnames(glioblastoma_counts), function(x) substring(x,2)))
# glioblastoma_metadata[,2] = rep('SmartSeq', dim(glioblastoma_counts)[2])
# glioblastoma_metadata[,3] = rep('TRUE', dim(glioblastoma_counts)[2])
# glioblastoma_metadata[,4] = substring(manifest$SUPPLIER.SAMPLE.NAME[match(glioblastoma_metadata$SampleName, manifest$SANGER.SAMPLE.ID)], 3, 4)
# patients = c('42','42','43', '43', '45', '45', '46', '46') # (info from sample tracker)
# geneNames = as.matrix(read.table(paste('../data/ZikaGlioblastomas/cellranger302_count_32771_5953STDY855119', as.character(1), '_GRCh38-3_0_0_premrna/filtered_feature_bc_matrix/filtered_feature_bc_matrix/features.tsv', sep = '')))
# 
# geneOccurence = table(geneNames[,2])
# for (gene in names(geneOccurence)){
#   if (geneOccurence[gene] > 1){
#     geneNames[which(geneNames[,2] == gene),2] = paste(geneNames[which(geneNames[,2] == gene),2], '(', geneNames[which(geneNames[,2] == gene),1], ')', sep = '')
#   }
# }
# rownames(glioblastoma_counts) = geneNames[match(rownames(glioblastoma_counts), geneNames[,1]),2]
# glioblastoma_counts = glioblastoma_counts[geneNames[,2],]
# 
# for (i in 1:8){
#   print(i)
#   # prefiltered count_matrix:
#   data_subset <- as.matrix(Read10X_h5(filename = paste('../data/HB_ZIK/HB_ZIK/cellranger302_count_32771_5953STDY855119', as.character(i), '_GRCh38-3_0_0_premrna/output_filtered.h5', sep = ''), use.names = TRUE))
#   sampleNames = rownames(data_subset)
#   glioblastoma_counts = cbind(glioblastoma_counts, data_subset)
#   metadata_subset = data.frame(matrix('', dim(data_subset)[2],4))
#   colnames(metadata_subset) = c('SampleName', 'Technology', 'ZikaExposure', 'Patient')
#   metadata_subset[,1] = colnames(data_subset)
#   metadata_subset[,2] = rep('10X', dim(data_subset)[2])
#   metadata_subset[,3] = rep('FALSE', dim(data_subset)[2])
#   metadata_subset[,4] = rep(patients[i], dim(data_subset)[2])
#   glioblastoma_metadata = rbind(glioblastoma_metadata, metadata_subset)
# }
# mitogenes <- genes(EnsDb.Hsapiens.v75, filter = ~ seq_name == "MT")$gene_id
# mitogenes = geneNames[,2][match(mitogenes, geneNames[,1])]
# mitogenes = mitogenes[!is.na(mitogenes)] 
# percent.mt = colSums(glioblastoma_counts[rownames(glioblastoma_counts) %in% mitogenes,])/colSums(glioblastoma_counts)
# Glioblastoma <- CreateSeuratObject(glioblastoma_counts, project = 'HB_ZIK', min.cells = 0, min.features = 0)
# Glioblastoma$SampleName = colnames(glioblastoma_counts)
# Glioblastoma$Technology = glioblastoma_metadata$Technology
# Glioblastoma$ZikaExposure = glioblastoma_metadata$ZikaExposure
# Glioblastoma$Patient = glioblastoma_metadata$Patient
# Glioblastoma$percent.mt = percent.mt
# saveRDS(Glioblastoma, file = "../data/ZikaGlioblastomas/zikaGlioblastomas_SeuratObject.rds")
Glioblastoma = readRDS("../data/ZikaGlioblastomas/zikaGlioblastomas_SeuratObject.rds")

The QC plots using number of detected genes, number of counts and percent of counts coming from mitochondrial genes (as a proxy for stress), show a couple of outlier cells, which I remove:

Glioblastoma.list <- SplitObject(Glioblastoma, split.by = 'Technology')
i = 1
VlnPlot(Glioblastoma.list[[i]], features = c("nFeature_RNA", "nCount_RNA", "percent.mt"), ncol = 3, group.by = 'Patient')

plot1 <- FeatureScatter(Glioblastoma.list[[i]], feature1 = "nCount_RNA", feature2 = "percent.mt")
plot2 <- FeatureScatter(Glioblastoma.list[[i]], feature1 = "nCount_RNA", feature2 = "nFeature_RNA")
CombinePlots(plots = list(plot1, plot2))

Glioblastoma.list[[i]] <- subset(Glioblastoma.list[[i]], subset = nFeature_RNA > 2500 & nFeature_RNA < 12000 & nCount_RNA < 2*10^6 & percent.mt < 0.1)
VlnPlot(Glioblastoma.list[[i]], features = c("nFeature_RNA", "nCount_RNA", "percent.mt"), ncol = 3, group.by = 'Patient')

i = 2
VlnPlot(Glioblastoma.list[[i]], features = c("nFeature_RNA", "nCount_RNA", "percent.mt"), ncol = 3, group.by = 'Patient')

plot1 <- FeatureScatter(Glioblastoma.list[[i]], feature1 = "nCount_RNA", feature2 = "percent.mt")
plot2 <- FeatureScatter(Glioblastoma.list[[i]], feature1 = "nCount_RNA", feature2 = "nFeature_RNA")
CombinePlots(plots = list(plot1, plot2))

Glioblastoma.list[[i]] <- subset(Glioblastoma.list[[i]], subset = nFeature_RNA > 500 & nFeature_RNA < 5000 & nCount_RNA > 0 & nCount_RNA < 4*10^5 & percent.mt < 0.1)
VlnPlot(Glioblastoma.list[[i]], features = c("nFeature_RNA", "nCount_RNA", "percent.mt"), ncol = 3, group.by = 'Patient')

The following normalizes, scales and select 2000 particularly variable genes.

for (i in 1:2){
Glioblastoma.list[[i]] <- NormalizeData(Glioblastoma.list[[i]], normalization.method = "LogNormalize", scale.factor = 10000)
Glioblastoma.list[[i]] <- FindVariableFeatures(Glioblastoma.list[[i]], selection.method = "vst", nfeatures = 2000)
top25 <- head(VariableFeatures(Glioblastoma.list[[i]]), 25)
plot1 <- VariableFeaturePlot(Glioblastoma.list[[i]])
plot2 <- LabelPoints(plot = plot1, points = top25, repel = TRUE)
CombinePlots(plots = list(plot1, plot2))
all.genes <- rownames(Glioblastoma.list[[i]])
Glioblastoma.list[[i]] <- ScaleData(Glioblastoma.list[[i]], features = all.genes)
}

These are the results of the PCA analysis:

for (i in 1:2){
Glioblastoma.list[[i]] <- RunPCA(Glioblastoma.list[[i]], features = VariableFeatures(object = Glioblastoma.list[[i]]))
print(Glioblastoma.list[[i]][["pca"]], dims = 1:5, nfeatures = 5)
VizDimLoadings(Glioblastoma.list[[i]], dims = 1:2, reduction = "pca")
DimPlot(Glioblastoma.list[[i]], reduction = "pca")
DimHeatmap(Glioblastoma.list[[i]], dims = 1, cells = round(dim(Glioblastoma.list[[i]])[2])/2, balanced = TRUE)
DimHeatmap(Glioblastoma.list[[i]], dims = 1:15, cells = round(dim(Glioblastoma.list[[i]])[2])/2, balanced = TRUE)
}
## PC_ 1 
## Positive:  MLLT3, LRP1B, LRRC4C, VXN, KCNQ5, BACH2, COPG2, DMD, CHN1, CADM2 
##     PDP1, ERBB4, TENT5A, VIPR2, GORAB, ZC3HAV1, ACSL3, ARL4A, OASL, FAM200A 
##     GPC6, PMAIP1, AC092691.1, AC092958.1, THUMPD3-AS1, HAS2, ZNF704, CFAP54, DLGAP1, HERC5 
## Negative:  FCER1G, TYROBP, CD74, SRGN, C1QC, LAPTM5, CTSB, APOE, GPNMB, AIF1 
##     CD14, C1QB, ITGB2, CTSS, HLA-DRA, CREG1, C1QA, PLXDC2, HLA-DRB1, FYB1 
##     APOC1, MS4A6A, TMEM176B, PILRA, PTPRC, SAMSN1, CTSL, HLA-DPA1, MSR1, S100A4 
## PC_ 2 
## Positive:  CKS1B, BIRC5, NUF2, TOP2A, PBK, PIMREG, CENPF, MAD2L1, SPC25, AURKB 
##     NUSAP1, CDC20, TPX2, UBE2C, SHCBP1, CDKN3, DLGAP5, HJURP, UBE2T, CKAP2L 
##     PTTG1, KIF23, TTK, BUB1B, CDCA3, AURKA, NDC80, KIF4A, CKAP2, CCNA2 
## Negative:  ZC3HAV1, IFI44, HERC5, VIPR2, OASL, AC015849.1, GCA, IFIH1, CFAP54, TNFAIP2 
##     AC118553.2, AL357060.1, AL356414.1, ART3, NFKBIZ, PDZD2, DHX58, PPM1K, IFNB1, DMD 
##     RSAD2, CDC14A, JAZF1-AS1, PLD5, GBP4, EPHA4, THUMPD3-AS1, PATL2, COPG2, BACH2 
## PC_ 3 
## Positive:  IGFBP7, SPARC, C1R, C1S, FN1, CLU, DLC1, CA12, COL1A1, F3 
##     CHI3L1, KDELR3, PTGFRN, COL6A2, DKK3, CDH11, CTSO, NOTCH3, PLA2G5, PKIG 
##     SELENOM, COL5A1, DCN, EGFR, COL4A1, PXDN, S100A16, PHLDA2, RAMP1, SERPINE2 
## Negative:  UBE2C, NUSAP1, NUF2, TOP2A, NDC80, ASPM, SGO1, TTK, ESCO2, BIRC5 
##     PBK, CDCA8, TPX2, AURKB, CCNB2, CKS2, KIF23, NCAPG, BUB1, CDC20 
##     CCNB1, DLGAP5, HJURP, NEK2, SKA1, CKAP2L, KIF2C, SKA3, CENPF, CDCA3 
## PC_ 4 
## Positive:  ANKS1B, KIF5A, SLC24A2, MAG, ZNF536, PEX5L, BCAS1, AKAP6, SLAIN1, UGT8 
##     ELDR, NRXN3, IL1RAPL1, PLP1, CNDP1, KLK6, DCTN2, AC004448.2, FOLH1, SPOCK3 
##     SYT1, PIP4K2C, ENPP2, TF, CDH19, GJB1, CNTNAP4, RPS2, SYT14, MOG 
## Negative:  TNFAIP6, TNFAIP2, GBP1, PMAIP1, BST2, HS3ST3B1, CCL2, CHI3L1, CHEK2, GBP3 
##     CD70, CPNE8, SAT1, FN1, IGFBP3, VCAM1, CXCL8, PHLDA2, MT2A, BIRC3 
##     WARS, HLA-E, GBP2, AXL, FAS, IFIH1, IGFBP6, CXCL3, IFITM2, TNFAIP8 
## PC_ 5 
## Positive:  EGFR, TENM3, SOCS2, RNF180, PTPRZ1, DDIT3, MEG3, NAMPT, PDPN, C2orf80 
##     MARS, ELDR, RAMP1, FABP7, MOXD1, TNC, PLK2, KIF5A, DTX3, PSRC1 
##     CADPS, METTL1, TSFM, ROBO2, TSHZ2, CLU, C1orf61, RGS6, CTDSP2, TSPAN31 
## Negative:  MYO1B, COL3A1, NDUFA4L2, LUM, DCN, COL1A2, EDNRA, PLAC9, BGN, COL1A1 
##     PDGFRB, RGS5(ENSG00000143248), PLXDC1, ITGA1, COL15A1, EDIL3, CAVIN3, IGFBP4, FAM162B, PRKG1 
##     UACA, NOTCH3, GNG11, ADGRF5, COL6A3, PRR16, LAMC3, TPM2, COL5A1, ENPEP 
## PC_ 1 
## Positive:  MLLT3, LRP1B, LRRC4C, VXN, KCNQ5 
## Negative:  FCER1G, TYROBP, CD74, SRGN, C1QC 
## PC_ 2 
## Positive:  CKS1B, BIRC5, NUF2, TOP2A, PBK 
## Negative:  ZC3HAV1, IFI44, HERC5, VIPR2, OASL 
## PC_ 3 
## Positive:  IGFBP7, SPARC, C1R, C1S, FN1 
## Negative:  UBE2C, NUSAP1, NUF2, TOP2A, NDC80 
## PC_ 4 
## Positive:  ANKS1B, KIF5A, SLC24A2, MAG, ZNF536 
## Negative:  TNFAIP6, TNFAIP2, GBP1, PMAIP1, BST2 
## PC_ 5 
## Positive:  EGFR, TENM3, SOCS2, RNF180, PTPRZ1 
## Negative:  MYO1B, COL3A1, NDUFA4L2, LUM, DCN

## PC_ 1 
## Positive:  SLC1A3, RNF220, CPM, SPP1, ST6GALNAC3, ST18, PDK4, TMEM144, RBM47, PLP1 
##     SLC11A1, NHSL1, TBXAS1, SLC9A9, ACSL1, CDK18, FYB1, SRGN, SLCO2B1, DOCK8 
##     MSR1, MOBP, APBB1IP, BNC2, BCAS1, FGFR2, CD74, SLC5A11, MERTK, AC074327.1 
## Negative:  DLGAP2, SYN2, CACNA1B, GALNT17, GRIN2A, SYN3, LINGO2, CNTN4, GABRG3, GABBR2 
##     LRFN5, GRIN2B, MYT1L, HS6ST3, CCSER1, GABRG2, CACNA1C, RIMBP2, CELF4, KHDRBS2 
##     RYR2, SYT1, AGBL4, RALYL, GABRB3, FRMPD4, GALNTL6, NETO1, PRR16, KCTD16 
## PC_ 2 
## Positive:  PLXDC2, SPP1, SLCO2B1, SRGN, PDK4, PRKAG2, ST6GALNAC3, ACSL1, MAN1A1, SLC11A1 
##     TBXAS1, APBB1IP, MSR1, DOCK8, FYB1, AC074327.1, ARHGAP15, CD74, MERTK, FMN1 
##     RBM47, BNC2, SYNJ2, CTSB, RAPGEF5, EPB41L3, LRMDA, CD163, SAT1, OLR1 
## Negative:  SOX6, NXPH1, PCDH15, LRRC4C, KCND2, MMP16, BRINP3, GRIK2, NKAIN3, SCN1A 
##     ETV1, SEMA6D, KAZN, LUZP2, AC004852.2, THSD7A, CA10, XKR4, DLGAP1, VCAN 
##     FGF14, AC092691.1, ERBB4, CNTN1, FGF12, GPC6, DGKG, SLC24A3, GLCCI1, IGF2BP3 
## PC_ 3 
## Positive:  SPOCK3, CNTNAP4, ST18, KIRREL3, PCSK6, ANK3, RNF220, TMEM144, PTPRD, PLP1 
##     BCAS1, MOBP, SLC5A11, CDK18, ANKS1B, CNDP1, DLC1, FGFR2, DLG2, ANO4 
##     HS3ST5, NRXN3, SYNJ2, LINC01170, RAPGEF5, AC026316.5, GALNT13, KCTD8, ST6GALNAC3, RASGRF2 
## Negative:  MT-CO1, MT-CO3, ITPR2, CELF2, SAT1, MT-CYB, SLC4A4, MT-ATP6, NAMPT, MT-ND4 
##     LRMDA, MT-CO2, SLC1A3, RBM47, RUNX1, NHSL1, VEGFA, MT-ND3, MT-ND1, PTCHD1-AS 
##     RGS6, APOE, SERPINE1, MT2A, MERTK, GLIS3, MT-ND2, SLC11A1, SHROOM3, SRGN 
## PC_ 4 
## Positive:  RGS6, SLC4A4, SHROOM3, VEGFA, CCT6A, NIPSNAP2, SUMF2, PTCHD1-AS, PHKG1, IGF1R 
##     MT2A, WWTR1, SEC61G, CHI3L1, PDZD2, ACSS3, LONRF2, LHFPL6, SYNJ2, PSPH 
##     RGS20, ALDH1L1, TNC, GPC5, IGFBP5, ARHGEF26, LAMA2, YAP1, ACSBG1, AKAP12 
## Negative:  FRMD4A, SRGN, APBB1IP, KCNQ3, SLCO2B1, SLC11A1, FMN1, AC074327.1, FYB1, TBXAS1 
##     MSR1, ARHGAP15, DOCK8, ST6GAL1, CD74, MERTK, ACSL1, MEF2C, TMEM163, LRMDA 
##     PLXDC2, CTSB, BNC2, TNS3, CD163, RBM47, OLR1, SAMSN1, SAT1, SPP1 
## PC_ 5 
## Positive:  GRIP1, SYNPR, SNRPN, GAD2, BTBD11, MGAT4C, ADAMTS9-AS2, MYRIP, ZMAT4, GRIA1 
##     FSTL5, SLC35F4, GRIN3A, LGI1, ADARB2, ZNF385D, CCDC85A, ZNF385B, C8orf34, ABLIM1 
##     PTPRM, HTR2C, RERG, MAST4, KCNAB1, MTUS2, INPP4B, TRPM3, NYAP2, HPSE2 
## Negative:  CA10, MMP16, MEGF11, TNR, AC004852.2, DGKB, DSCAM, PCDH15, XYLT1, IGF2BP3 
##     ETV1, BRINP3, GALNT13, GLCCI1, CSMD1, VCAN, ADAMTSL1, NXPH1, NTN1, BCAN 
##     EYA1, KHDRBS3, ZFPM2, DLGAP1, CSMD3, GRIA4, PCDH11X, AC016205.1, FGF12, TNS3 
## PC_ 1 
## Positive:  SLC1A3, RNF220, CPM, SPP1, ST6GALNAC3 
## Negative:  DLGAP2, SYN2, CACNA1B, GALNT17, GRIN2A 
## PC_ 2 
## Positive:  PLXDC2, SPP1, SLCO2B1, SRGN, PDK4 
## Negative:  SOX6, NXPH1, PCDH15, LRRC4C, KCND2 
## PC_ 3 
## Positive:  SPOCK3, CNTNAP4, ST18, KIRREL3, PCSK6 
## Negative:  MT-CO1, MT-CO3, ITPR2, CELF2, SAT1 
## PC_ 4 
## Positive:  RGS6, SLC4A4, SHROOM3, VEGFA, CCT6A 
## Negative:  FRMD4A, SRGN, APBB1IP, KCNQ3, SLCO2B1 
## PC_ 5 
## Positive:  GRIP1, SYNPR, SNRPN, GAD2, BTBD11 
## Negative:  CA10, MMP16, MEGF11, TNR, AC004852.2

Based on the JackStraw procedure I select 14 PCs for further analysis in both cases:

# for (i in 1:2){
# Glioblastoma.list[[i]] <- JackStraw(Glioblastoma.list[[i]], num.replicate = 100)
# Glioblastoma.list[[i]] <- ScoreJackStraw(Glioblastoma.list[[i]], dims = 1:20)
# JackStrawPlot(Glioblastoma.list[[i]], dims = 1:20)
# ElbowPlot(Glioblastoma.list[[i]], ndims = 40)
# }

This is the clustering step:

n_dimensions = 14
for (i in 1:2){
Glioblastoma.list[[i]] <- FindNeighbors(Glioblastoma.list[[i]], dims = 1:n_dimensions)
Glioblastoma.list[[i]] <- FindClusters(Glioblastoma.list[[i]], resolution = 0.5)
head(Idents(Glioblastoma.list[[i]]), 5)
}
## Modularity Optimizer version 1.3.0 by Ludo Waltman and Nees Jan van Eck
## 
## Number of nodes: 1163
## Number of edges: 33145
## 
## Running Louvain algorithm...
## Maximum modularity in 10 random starts: 0.9066
## Number of communities: 12
## Elapsed time: 0 seconds
## Modularity Optimizer version 1.3.0 by Ludo Waltman and Nees Jan van Eck
## 
## Number of nodes: 31755
## Number of edges: 1081205
## 
## Running Louvain algorithm...
## Maximum modularity in 10 random starts: 0.9437
## Number of communities: 23
## Elapsed time: 6 seconds

Clusters roughly agree with visual seperation on a UMAP plot:

for (i in 1:2){
Glioblastoma.list[[i]] <- RunUMAP(Glioblastoma.list[[i]], dims = 1:n_dimensions)
DimPlot(Glioblastoma.list[[i]], reduction = "umap")
#saveRDS(axonGrowth, file = "axonGrowth_SeuratTutorial.rds")
}

Visualize markers and annotate clusters:

i = 1
#Glioblastoma.0.markers <- FindAllMarkers(Glioblastoma.list[[i]], only.pos = TRUE, min.pct = 0.25, logfc.threshold = 0.25)
#saveRDS(Glioblastoma.0.markers, file = "../data/ZikaGlioblastomas/Glioblastoma.0.markers.rds")
Glioblastoma.0.markers = readRDS("../data/ZikaGlioblastomas/Glioblastoma.0.markers.rds")
top = Glioblastoma.0.markers %>% group_by(cluster) %>% top_n(n = 1, wt = avg_logFC)
FeaturePlot(Glioblastoma.list[[i]], features = top$gene)

top10 <- Glioblastoma.0.markers %>% group_by(cluster) %>% top_n(n = 10, wt = avg_logFC)
DoHeatmap(Glioblastoma.list[[i]], features = top10$gene, cells = 1:dim(Glioblastoma.list[[i]])[2] + NoLegend())

as.matrix(top10)  
##        p_val           avg_logFC  pct.1   pct.2   p_val_adj       cluster
##   [1,] "2.798759e-128" "2.522756" "0.989" "0.223" "9.386477e-124" "0"    
##   [2,] "3.527754e-128" "2.129951" "0.983" "0.205" "1.183138e-123" "0"    
##   [3,] "2.478211e-124" "2.329936" "0.989" "0.225" "8.311422e-120" "0"    
##   [4,] "1.318814e-118" "2.133787" "0.994" "0.250" "4.423038e-114" "0"    
##   [5,] "3.134785e-115" "2.228971" "1.000" "0.291" "1.051344e-110" "0"    
##   [6,] "1.355377e-114" "2.567080" "0.989" "0.282" "4.545664e-110" "0"    
##   [7,] "5.912241e-114" "2.169436" "1.000" "0.295" "1.982847e-109" "0"    
##   [8,] "8.787250e-112" "2.700498" "1.000" "0.311" "2.947068e-107" "0"    
##   [9,] "2.518811e-111" "2.143144" "0.994" "0.262" "8.447589e-107" "0"    
##  [10,] "3.723965e-104" "2.103426" "1.000" "0.395" " 1.248943e-99" "0"    
##  [11,] " 5.390725e-81" "2.038185" "0.953" "0.331" " 1.807941e-76" "1"    
##  [12,] " 3.096750e-73" "1.818058" "0.935" "0.381" " 1.038588e-68" "1"    
##  [13,] " 2.787820e-66" "1.946037" "1.000" "0.759" " 9.349790e-62" "1"    
##  [14,] " 3.809341e-66" "1.423535" "0.923" "0.395" " 1.277577e-61" "1"    
##  [15,] " 3.939624e-62" "1.408315" "0.994" "0.745" " 1.321271e-57" "1"    
##  [16,] " 2.026466e-57" "1.497978" "0.905" "0.420" " 6.796361e-53" "1"    
##  [17,] " 6.328998e-57" "1.633480" "0.970" "0.755" " 2.122619e-52" "1"    
##  [18,] " 1.866497e-56" "1.511335" "0.988" "0.830" " 6.259857e-52" "1"    
##  [19,] " 4.110477e-53" "1.550033" "0.923" "0.597" " 1.378572e-48" "1"    
##  [20,] " 1.494263e-51" "1.516664" "0.982" "0.624" " 5.011461e-47" "1"    
##  [21,] " 7.497445e-78" "1.826130" "0.721" "0.121" " 2.514493e-73" "2"    
##  [22,] " 1.846264e-74" "2.391872" "0.994" "0.897" " 6.192000e-70" "2"    
##  [23,] " 5.179022e-72" "1.623937" "0.864" "0.240" " 1.736940e-67" "2"    
##  [24,] " 2.527806e-60" "1.413136" "0.974" "0.812" " 8.477756e-56" "2"    
##  [25,] " 5.903210e-60" "1.469367" "0.935" "0.507" " 1.979819e-55" "2"    
##  [26,] " 5.530687e-59" "1.790494" "1.000" "0.927" " 1.854882e-54" "2"    
##  [27,] " 3.788774e-57" "1.937084" "0.981" "0.700" " 1.270679e-52" "2"    
##  [28,] " 1.882958e-56" "1.495411" "1.000" "0.996" " 6.315065e-52" "2"    
##  [29,] " 2.766177e-51" "1.440902" "0.714" "0.177" " 9.277206e-47" "2"    
##  [30,] " 1.948553e-47" "1.448895" "0.948" "0.670" " 6.535057e-43" "2"    
##  [31,] "2.696909e-170" "1.536410" "0.930" "0.051" "9.044894e-166" "3"    
##  [32,] " 1.813295e-97" "1.715417" "0.937" "0.228" " 6.081429e-93" "3"    
##  [33,] " 8.325655e-88" "1.961581" "0.965" "0.282" " 2.792258e-83" "3"    
##  [34,] " 2.807664e-79" "1.836803" "0.986" "0.546" " 9.416344e-75" "3"    
##  [35,] " 4.265136e-76" "1.904044" "0.986" "0.601" " 1.430441e-71" "3"    
##  [36,] " 4.129375e-75" "1.849851" "0.993" "0.638" " 1.384910e-70" "3"    
##  [37,] " 9.078462e-75" "2.576137" "0.986" "0.773" " 3.044735e-70" "3"    
##  [38,] " 9.823225e-75" "2.063922" "0.986" "0.614" " 3.294513e-70" "3"    
##  [39,] " 6.953299e-73" "1.886080" "0.972" "0.537" " 2.331997e-68" "3"    
##  [40,] " 2.234984e-68" "2.417912" "0.986" "0.758" " 7.495690e-64" "3"    
##  [41,] " 1.167120e-54" "2.252501" "0.790" "0.206" " 3.914288e-50" "4"    
##  [42,] " 4.401099e-52" "1.387220" "0.975" "0.512" " 1.476040e-47" "4"    
##  [43,] " 2.148337e-45" "1.450118" "0.840" "0.307" " 7.205092e-41" "4"    
##  [44,] " 2.076797e-42" "2.257484" "0.933" "0.476" " 6.965162e-38" "4"    
##  [45,] " 1.702096e-41" "1.615830" "0.874" "0.416" " 5.708489e-37" "4"    
##  [46,] " 2.759173e-41" "1.452258" "0.916" "0.527" " 9.253714e-37" "4"    
##  [47,] " 1.176994e-39" "1.446625" "0.975" "0.628" " 3.947404e-35" "4"    
##  [48,] " 2.298906e-34" "1.633594" "1.000" "0.975" " 7.710072e-30" "4"    
##  [49,] " 2.241069e-21" "1.797888" "0.773" "0.444" " 7.516096e-17" "4"    
##  [50,] " 1.221268e-18" "1.444292" "0.672" "0.342" " 4.095887e-14" "4"    
##  [51,] " 7.918077e-48" "1.622165" "0.990" "0.431" " 2.655565e-43" "5"    
##  [52,] " 2.238636e-46" "1.696176" "1.000" "0.722" " 7.507939e-42" "5"    
##  [53,] " 2.860564e-43" "1.459257" "0.929" "0.404" " 9.593760e-39" "5"    
##  [54,] " 4.813143e-41" "1.435189" "0.848" "0.277" " 1.614232e-36" "5"    
##  [55,] " 3.354506e-40" "1.458001" "0.909" "0.391" " 1.125034e-35" "5"    
##  [56,] " 5.105091e-40" "1.447743" "1.000" "0.790" " 1.712145e-35" "5"    
##  [57,] " 1.080295e-23" "1.418654" "0.899" "0.719" " 3.623092e-19" "5"    
##  [58,] " 1.197681e-20" "1.753500" "1.000" "0.996" " 4.016783e-16" "5"    
##  [59,] " 1.312912e-11" "1.967047" "0.980" "0.955" " 4.403245e-07" "5"    
##  [60,] " 1.819123e-06" "1.646971" "0.545" "0.420" " 6.100973e-02" "5"    
##  [61,] " 1.947917e-52" "1.186712" "0.922" "0.288" " 6.532923e-48" "6"    
##  [62,] " 2.604675e-46" "1.484916" "0.956" "0.408" " 8.735558e-42" "6"    
##  [63,] " 5.102311e-43" "1.315888" "0.933" "0.437" " 1.711213e-38" "6"    
##  [64,] " 1.494108e-42" "1.580178" "0.833" "0.266" " 5.010940e-38" "6"    
##  [65,] " 1.421163e-39" "1.139706" "0.889" "0.391" " 4.766297e-35" "6"    
##  [66,] " 7.483431e-39" "1.488748" "0.800" "0.228" " 2.509793e-34" "6"    
##  [67,] " 3.977564e-38" "1.387418" "0.989" "0.712" " 1.333995e-33" "6"    
##  [68,] " 1.357131e-32" "1.878086" "1.000" "0.931" " 4.551547e-28" "6"    
##  [69,] " 1.628702e-28" "1.268166" "0.900" "0.584" " 5.462342e-24" "6"    
##  [70,] " 3.900800e-26" "1.294382" "0.956" "0.689" " 1.308250e-21" "6"    
##  [71,] " 8.572137e-90" "1.768726" "1.000" "0.130" " 2.874923e-85" "7"    
##  [72,] " 1.368958e-87" "2.042924" "0.985" "0.129" " 4.591212e-83" "7"    
##  [73,] " 5.452865e-87" "2.236550" "0.985" "0.129" " 1.828782e-82" "7"    
##  [74,] " 3.346281e-64" "1.856521" "0.985" "0.221" " 1.122276e-59" "7"    
##  [75,] " 6.084572e-58" "1.687365" "0.970" "0.235" " 2.040644e-53" "7"    
##  [76,] " 9.481351e-58" "2.451641" "1.000" "0.285" " 3.179856e-53" "7"    
##  [77,] " 4.857875e-55" "2.280891" "0.924" "0.205" " 1.629234e-50" "7"    
##  [78,] " 2.406805e-41" "1.880665" "1.000" "0.538" " 8.071942e-37" "7"    
##  [79,] " 4.244582e-41" "1.753201" "1.000" "0.505" " 1.423548e-36" "7"    
##  [80,] " 4.642748e-36" "1.927642" "1.000" "0.633" " 1.557085e-31" "7"    
##  [81,] " 1.119942e-30" "1.613989" "0.723" "0.184" " 3.756061e-26" "8"    
##  [82,] " 2.331677e-29" "1.476633" "0.985" "0.648" " 7.819977e-25" "8"    
##  [83,] " 3.164093e-29" "1.066209" "0.954" "0.427" " 1.061174e-24" "8"    
##  [84,] " 4.007181e-29" "1.297525" "0.985" "0.649" " 1.343928e-24" "8"    
##  [85,] " 1.213273e-28" "1.408490" "0.985" "0.666" " 4.069074e-24" "8"    
##  [86,] " 1.192655e-25" "1.062717" "1.000" "0.855" " 3.999926e-21" "8"    
##  [87,] " 3.896175e-25" "1.414331" "1.000" "0.788" " 1.306699e-20" "8"    
##  [88,] " 8.366594e-24" "1.160669" "1.000" "0.912" " 2.805988e-19" "8"    
##  [89,] " 2.247137e-22" "1.263117" "0.846" "0.299" " 7.536448e-18" "8"    
##  [90,] " 2.352472e-17" "1.046039" "0.954" "0.643" " 7.889721e-13" "8"    
##  [91,] " 1.735046e-63" "3.263369" "0.917" "0.118" " 5.818996e-59" "9"    
##  [92,] " 2.762613e-55" "2.569412" "0.979" "0.189" " 9.265251e-51" "9"    
##  [93,] " 6.419675e-44" "2.227550" "0.771" "0.120" " 2.153031e-39" "9"    
##  [94,] " 6.937651e-42" "2.623658" "0.958" "0.267" " 2.326749e-37" "9"    
##  [95,] " 2.289617e-38" "2.592318" "0.938" "0.279" " 7.678916e-34" "9"    
##  [96,] " 8.660222e-32" "3.175171" "1.000" "0.752" " 2.904465e-27" "9"    
##  [97,] " 6.690497e-26" "2.182278" "1.000" "0.664" " 2.243859e-21" "9"    
##  [98,] " 2.150475e-19" "2.240637" "0.875" "0.457" " 7.212262e-15" "9"    
##  [99,] " 3.674938e-19" "2.320411" "0.958" "0.618" " 1.232501e-14" "9"    
## [100,] " 7.397930e-19" "2.200289" "0.958" "0.921" " 2.481118e-14" "9"    
## [101,] "1.551403e-165" "2.860848" "1.000" "0.009" "5.203095e-161" "10"   
## [102,] " 9.468058e-83" "3.255233" "1.000" "0.035" " 3.175397e-78" "10"   
## [103,] " 1.487256e-55" "3.158075" "1.000" "0.063" " 4.987960e-51" "10"   
## [104,] " 5.362388e-38" "3.206616" "1.000" "0.107" " 1.798438e-33" "10"   
## [105,] " 1.073640e-34" "2.909807" "0.833" "0.074" " 3.600772e-30" "10"   
## [106,] " 3.716395e-31" "2.749332" "0.667" "0.049" " 1.246404e-26" "10"   
## [107,] " 3.859706e-17" "2.549649" "1.000" "0.351" " 1.294468e-12" "10"   
## [108,] " 1.293738e-16" "2.597582" "1.000" "0.334" " 4.338939e-12" "10"   
## [109,] " 1.510370e-14" "3.835891" "1.000" "0.520" " 5.065478e-10" "10"   
## [110,] " 2.953189e-13" "2.547447" "1.000" "0.646" " 9.904404e-09" "10"   
## [111,] "3.528310e-157" "2.182565" "0.923" "0.005" "1.183325e-152" "11"   
## [112,] "1.124497e-149" "1.528145" "0.923" "0.006" "3.771338e-145" "11"   
## [113,] "1.194096e-132" "2.276899" "0.846" "0.006" "4.004759e-128" "11"   
## [114,] " 4.843226e-88" "1.969147" "1.000" "0.023" " 1.624321e-83" "11"   
## [115,] " 6.342572e-46" "1.954123" "1.000" "0.056" " 2.127172e-41" "11"   
## [116,] " 1.077809e-24" "1.833355" "1.000" "0.130" " 3.614755e-20" "11"   
## [117,] " 1.717758e-15" "1.884843" "0.846" "0.127" " 5.761015e-11" "11"   
## [118,] " 7.243264e-12" "1.603618" "1.000" "0.341" " 2.429246e-07" "11"   
## [119,] " 5.239166e-11" "1.499413" "0.615" "0.104" " 1.757112e-06" "11"   
## [120,] " 8.042425e-10" "1.536496" "0.923" "0.298" " 2.697268e-05" "11"   
##        gene        
##   [1,] "C1QC"      
##   [2,] "C1QA"      
##   [3,] "C1QB"      
##   [4,] "HLA-DRB1"  
##   [5,] "FCER1G"    
##   [6,] "CD14"      
##   [7,] "SRGN"      
##   [8,] "CD74"      
##   [9,] "HLA-DRA"   
##  [10,] "LAPTM5"    
##  [11,] "PMAIP1"    
##  [12,] "TNFAIP6"   
##  [13,] "LRP1B"     
##  [14,] "BIRC3"     
##  [15,] "NAV2"      
##  [16,] "PLK2"      
##  [17,] "TTC28"     
##  [18,] "ACSL3"     
##  [19,] "PPP1R15A"  
##  [20,] "EGFR"      
##  [21,] "HIST1H4E"  
##  [22,] "CNTNAP2"   
##  [23,] "HIST1H4H"  
##  [24,] "PCDH11X"   
##  [25,] "ADAMTSL1"  
##  [26,] "DLGAP1"    
##  [27,] "KCNQ5"     
##  [28,] "DMD"       
##  [29,] "IFNB1"     
##  [30,] "COPG2"     
##  [31,] "ELDR"      
##  [32,] "DTX3"      
##  [33,] "CADPS"     
##  [34,] "KIF5A"     
##  [35,] "AC084033.3"
##  [36,] "CDK4"      
##  [37,] "MARS"      
##  [38,] "DCTN2"     
##  [39,] "TSPAN31"   
##  [40,] "DDIT3"     
##  [41,] "IGFBP3"    
##  [42,] "MSMO1"     
##  [43,] "HOPX"      
##  [44,] "CHI3L1"    
##  [45,] "ATP1B2"    
##  [46,] "GATM"      
##  [47,] "RCAN1"     
##  [48,] "PTPRZ1"    
##  [49,] "SERPINE1"  
##  [50,] "AGT"       
##  [51,] "PLXDC2"    
##  [52,] "LRMDA"     
##  [53,] "FMN1"      
##  [54,] "AC074327.1"
##  [55,] "EPB41L3"   
##  [56,] "DOCK4"     
##  [57,] "DAPK1"     
##  [58,] "SCHLAP1"   
##  [59,] "ASCC2"     
##  [60,] "GFRA2"     
##  [61,] "NTNG1"     
##  [62,] "ID1"       
##  [63,] "GPC5"      
##  [64,] "FAM155A"   
##  [65,] "MGST1"     
##  [66,] "METTL7B"   
##  [67,] "CTNNA2"    
##  [68,] "SEC61G"    
##  [69,] "S100A16"   
##  [70,] "ANXA1"     
##  [71,] "BIRC5"     
##  [72,] "UBE2C"     
##  [73,] "TOP2A"     
##  [74,] "TPX2"      
##  [75,] "CENPF"     
##  [76,] "NUSAP1"    
##  [77,] "CCNB1"     
##  [78,] "PTTG1"     
##  [79,] "CKS2"      
##  [80,] "KPNA2"     
##  [81,] "CTGF"      
##  [82,] "ACAT2"     
##  [83,] "NTRK2"     
##  [84,] "FDFT1"     
##  [85,] "DGKB"      
##  [86,] "GAP43"     
##  [87,] "PTN"       
##  [88,] "TUBA1A"    
##  [89,] "GAL"       
##  [90,] "FABP7"     
##  [91,] "PLP1"      
##  [92,] "BCAS1"     
##  [93,] "TF"        
##  [94,] "SLAIN1"    
##  [95,] "CYB5R2"    
##  [96,] "AKAP6"     
##  [97,] "CRYAB"     
##  [98,] "CA2"       
##  [99,] "S100B"     
## [100,] "GLUL"      
## [101,] "COL3A1"    
## [102,] "DCN"       
## [103,] "NDUFA4L2"  
## [104,] "COL1A2"    
## [105,] "COL1A1"    
## [106,] "STC1"      
## [107,] "COL4A1"    
## [108,] "FSTL1"     
## [109,] "FN1"       
## [110,] "SPARC"     
## [111,] "CD2"       
## [112,] "TRBC2"     
## [113,] "GZMA"      
## [114,] "CD52"      
## [115,] "TRAC"      
## [116,] "CD96"      
## [117,] "CCL4"      
## [118,] "PTPRC"     
## [119,] "TC2N"      
## [120,] "PCED1B"
i = 2
#Glioblastoma.1.markers <- FindAllMarkers(Glioblastoma.list[[i]], only.pos = TRUE, min.pct = 0.25, logfc.threshold = 0.25)
#saveRDS(Glioblastoma.1.markers, file = "../data/ZikaGlioblastomas/Glioblastoma.1.markers.rds")
Glioblastoma.1.markers = readRDS("../data/ZikaGlioblastomas/Glioblastoma.1.markers.rds")
top = Glioblastoma.1.markers %>% group_by(cluster) %>% top_n(n = 1, wt = avg_logFC)
FeaturePlot(Glioblastoma.list[[i]], features = top$gene)

top5 <- Glioblastoma.1.markers %>% group_by(cluster) %>% top_n(n = 5, wt = avg_logFC)
DoHeatmap(Glioblastoma.list[[i]], features = top5$gene, cells = sample(1:dim(Glioblastoma.list[[i]])[2], 1000))

as.matrix(top10)
##        p_val           avg_logFC  pct.1   pct.2   p_val_adj       cluster
##   [1,] "2.798759e-128" "2.522756" "0.989" "0.223" "9.386477e-124" "0"    
##   [2,] "3.527754e-128" "2.129951" "0.983" "0.205" "1.183138e-123" "0"    
##   [3,] "2.478211e-124" "2.329936" "0.989" "0.225" "8.311422e-120" "0"    
##   [4,] "1.318814e-118" "2.133787" "0.994" "0.250" "4.423038e-114" "0"    
##   [5,] "3.134785e-115" "2.228971" "1.000" "0.291" "1.051344e-110" "0"    
##   [6,] "1.355377e-114" "2.567080" "0.989" "0.282" "4.545664e-110" "0"    
##   [7,] "5.912241e-114" "2.169436" "1.000" "0.295" "1.982847e-109" "0"    
##   [8,] "8.787250e-112" "2.700498" "1.000" "0.311" "2.947068e-107" "0"    
##   [9,] "2.518811e-111" "2.143144" "0.994" "0.262" "8.447589e-107" "0"    
##  [10,] "3.723965e-104" "2.103426" "1.000" "0.395" " 1.248943e-99" "0"    
##  [11,] " 5.390725e-81" "2.038185" "0.953" "0.331" " 1.807941e-76" "1"    
##  [12,] " 3.096750e-73" "1.818058" "0.935" "0.381" " 1.038588e-68" "1"    
##  [13,] " 2.787820e-66" "1.946037" "1.000" "0.759" " 9.349790e-62" "1"    
##  [14,] " 3.809341e-66" "1.423535" "0.923" "0.395" " 1.277577e-61" "1"    
##  [15,] " 3.939624e-62" "1.408315" "0.994" "0.745" " 1.321271e-57" "1"    
##  [16,] " 2.026466e-57" "1.497978" "0.905" "0.420" " 6.796361e-53" "1"    
##  [17,] " 6.328998e-57" "1.633480" "0.970" "0.755" " 2.122619e-52" "1"    
##  [18,] " 1.866497e-56" "1.511335" "0.988" "0.830" " 6.259857e-52" "1"    
##  [19,] " 4.110477e-53" "1.550033" "0.923" "0.597" " 1.378572e-48" "1"    
##  [20,] " 1.494263e-51" "1.516664" "0.982" "0.624" " 5.011461e-47" "1"    
##  [21,] " 7.497445e-78" "1.826130" "0.721" "0.121" " 2.514493e-73" "2"    
##  [22,] " 1.846264e-74" "2.391872" "0.994" "0.897" " 6.192000e-70" "2"    
##  [23,] " 5.179022e-72" "1.623937" "0.864" "0.240" " 1.736940e-67" "2"    
##  [24,] " 2.527806e-60" "1.413136" "0.974" "0.812" " 8.477756e-56" "2"    
##  [25,] " 5.903210e-60" "1.469367" "0.935" "0.507" " 1.979819e-55" "2"    
##  [26,] " 5.530687e-59" "1.790494" "1.000" "0.927" " 1.854882e-54" "2"    
##  [27,] " 3.788774e-57" "1.937084" "0.981" "0.700" " 1.270679e-52" "2"    
##  [28,] " 1.882958e-56" "1.495411" "1.000" "0.996" " 6.315065e-52" "2"    
##  [29,] " 2.766177e-51" "1.440902" "0.714" "0.177" " 9.277206e-47" "2"    
##  [30,] " 1.948553e-47" "1.448895" "0.948" "0.670" " 6.535057e-43" "2"    
##  [31,] "2.696909e-170" "1.536410" "0.930" "0.051" "9.044894e-166" "3"    
##  [32,] " 1.813295e-97" "1.715417" "0.937" "0.228" " 6.081429e-93" "3"    
##  [33,] " 8.325655e-88" "1.961581" "0.965" "0.282" " 2.792258e-83" "3"    
##  [34,] " 2.807664e-79" "1.836803" "0.986" "0.546" " 9.416344e-75" "3"    
##  [35,] " 4.265136e-76" "1.904044" "0.986" "0.601" " 1.430441e-71" "3"    
##  [36,] " 4.129375e-75" "1.849851" "0.993" "0.638" " 1.384910e-70" "3"    
##  [37,] " 9.078462e-75" "2.576137" "0.986" "0.773" " 3.044735e-70" "3"    
##  [38,] " 9.823225e-75" "2.063922" "0.986" "0.614" " 3.294513e-70" "3"    
##  [39,] " 6.953299e-73" "1.886080" "0.972" "0.537" " 2.331997e-68" "3"    
##  [40,] " 2.234984e-68" "2.417912" "0.986" "0.758" " 7.495690e-64" "3"    
##  [41,] " 1.167120e-54" "2.252501" "0.790" "0.206" " 3.914288e-50" "4"    
##  [42,] " 4.401099e-52" "1.387220" "0.975" "0.512" " 1.476040e-47" "4"    
##  [43,] " 2.148337e-45" "1.450118" "0.840" "0.307" " 7.205092e-41" "4"    
##  [44,] " 2.076797e-42" "2.257484" "0.933" "0.476" " 6.965162e-38" "4"    
##  [45,] " 1.702096e-41" "1.615830" "0.874" "0.416" " 5.708489e-37" "4"    
##  [46,] " 2.759173e-41" "1.452258" "0.916" "0.527" " 9.253714e-37" "4"    
##  [47,] " 1.176994e-39" "1.446625" "0.975" "0.628" " 3.947404e-35" "4"    
##  [48,] " 2.298906e-34" "1.633594" "1.000" "0.975" " 7.710072e-30" "4"    
##  [49,] " 2.241069e-21" "1.797888" "0.773" "0.444" " 7.516096e-17" "4"    
##  [50,] " 1.221268e-18" "1.444292" "0.672" "0.342" " 4.095887e-14" "4"    
##  [51,] " 7.918077e-48" "1.622165" "0.990" "0.431" " 2.655565e-43" "5"    
##  [52,] " 2.238636e-46" "1.696176" "1.000" "0.722" " 7.507939e-42" "5"    
##  [53,] " 2.860564e-43" "1.459257" "0.929" "0.404" " 9.593760e-39" "5"    
##  [54,] " 4.813143e-41" "1.435189" "0.848" "0.277" " 1.614232e-36" "5"    
##  [55,] " 3.354506e-40" "1.458001" "0.909" "0.391" " 1.125034e-35" "5"    
##  [56,] " 5.105091e-40" "1.447743" "1.000" "0.790" " 1.712145e-35" "5"    
##  [57,] " 1.080295e-23" "1.418654" "0.899" "0.719" " 3.623092e-19" "5"    
##  [58,] " 1.197681e-20" "1.753500" "1.000" "0.996" " 4.016783e-16" "5"    
##  [59,] " 1.312912e-11" "1.967047" "0.980" "0.955" " 4.403245e-07" "5"    
##  [60,] " 1.819123e-06" "1.646971" "0.545" "0.420" " 6.100973e-02" "5"    
##  [61,] " 1.947917e-52" "1.186712" "0.922" "0.288" " 6.532923e-48" "6"    
##  [62,] " 2.604675e-46" "1.484916" "0.956" "0.408" " 8.735558e-42" "6"    
##  [63,] " 5.102311e-43" "1.315888" "0.933" "0.437" " 1.711213e-38" "6"    
##  [64,] " 1.494108e-42" "1.580178" "0.833" "0.266" " 5.010940e-38" "6"    
##  [65,] " 1.421163e-39" "1.139706" "0.889" "0.391" " 4.766297e-35" "6"    
##  [66,] " 7.483431e-39" "1.488748" "0.800" "0.228" " 2.509793e-34" "6"    
##  [67,] " 3.977564e-38" "1.387418" "0.989" "0.712" " 1.333995e-33" "6"    
##  [68,] " 1.357131e-32" "1.878086" "1.000" "0.931" " 4.551547e-28" "6"    
##  [69,] " 1.628702e-28" "1.268166" "0.900" "0.584" " 5.462342e-24" "6"    
##  [70,] " 3.900800e-26" "1.294382" "0.956" "0.689" " 1.308250e-21" "6"    
##  [71,] " 8.572137e-90" "1.768726" "1.000" "0.130" " 2.874923e-85" "7"    
##  [72,] " 1.368958e-87" "2.042924" "0.985" "0.129" " 4.591212e-83" "7"    
##  [73,] " 5.452865e-87" "2.236550" "0.985" "0.129" " 1.828782e-82" "7"    
##  [74,] " 3.346281e-64" "1.856521" "0.985" "0.221" " 1.122276e-59" "7"    
##  [75,] " 6.084572e-58" "1.687365" "0.970" "0.235" " 2.040644e-53" "7"    
##  [76,] " 9.481351e-58" "2.451641" "1.000" "0.285" " 3.179856e-53" "7"    
##  [77,] " 4.857875e-55" "2.280891" "0.924" "0.205" " 1.629234e-50" "7"    
##  [78,] " 2.406805e-41" "1.880665" "1.000" "0.538" " 8.071942e-37" "7"    
##  [79,] " 4.244582e-41" "1.753201" "1.000" "0.505" " 1.423548e-36" "7"    
##  [80,] " 4.642748e-36" "1.927642" "1.000" "0.633" " 1.557085e-31" "7"    
##  [81,] " 1.119942e-30" "1.613989" "0.723" "0.184" " 3.756061e-26" "8"    
##  [82,] " 2.331677e-29" "1.476633" "0.985" "0.648" " 7.819977e-25" "8"    
##  [83,] " 3.164093e-29" "1.066209" "0.954" "0.427" " 1.061174e-24" "8"    
##  [84,] " 4.007181e-29" "1.297525" "0.985" "0.649" " 1.343928e-24" "8"    
##  [85,] " 1.213273e-28" "1.408490" "0.985" "0.666" " 4.069074e-24" "8"    
##  [86,] " 1.192655e-25" "1.062717" "1.000" "0.855" " 3.999926e-21" "8"    
##  [87,] " 3.896175e-25" "1.414331" "1.000" "0.788" " 1.306699e-20" "8"    
##  [88,] " 8.366594e-24" "1.160669" "1.000" "0.912" " 2.805988e-19" "8"    
##  [89,] " 2.247137e-22" "1.263117" "0.846" "0.299" " 7.536448e-18" "8"    
##  [90,] " 2.352472e-17" "1.046039" "0.954" "0.643" " 7.889721e-13" "8"    
##  [91,] " 1.735046e-63" "3.263369" "0.917" "0.118" " 5.818996e-59" "9"    
##  [92,] " 2.762613e-55" "2.569412" "0.979" "0.189" " 9.265251e-51" "9"    
##  [93,] " 6.419675e-44" "2.227550" "0.771" "0.120" " 2.153031e-39" "9"    
##  [94,] " 6.937651e-42" "2.623658" "0.958" "0.267" " 2.326749e-37" "9"    
##  [95,] " 2.289617e-38" "2.592318" "0.938" "0.279" " 7.678916e-34" "9"    
##  [96,] " 8.660222e-32" "3.175171" "1.000" "0.752" " 2.904465e-27" "9"    
##  [97,] " 6.690497e-26" "2.182278" "1.000" "0.664" " 2.243859e-21" "9"    
##  [98,] " 2.150475e-19" "2.240637" "0.875" "0.457" " 7.212262e-15" "9"    
##  [99,] " 3.674938e-19" "2.320411" "0.958" "0.618" " 1.232501e-14" "9"    
## [100,] " 7.397930e-19" "2.200289" "0.958" "0.921" " 2.481118e-14" "9"    
## [101,] "1.551403e-165" "2.860848" "1.000" "0.009" "5.203095e-161" "10"   
## [102,] " 9.468058e-83" "3.255233" "1.000" "0.035" " 3.175397e-78" "10"   
## [103,] " 1.487256e-55" "3.158075" "1.000" "0.063" " 4.987960e-51" "10"   
## [104,] " 5.362388e-38" "3.206616" "1.000" "0.107" " 1.798438e-33" "10"   
## [105,] " 1.073640e-34" "2.909807" "0.833" "0.074" " 3.600772e-30" "10"   
## [106,] " 3.716395e-31" "2.749332" "0.667" "0.049" " 1.246404e-26" "10"   
## [107,] " 3.859706e-17" "2.549649" "1.000" "0.351" " 1.294468e-12" "10"   
## [108,] " 1.293738e-16" "2.597582" "1.000" "0.334" " 4.338939e-12" "10"   
## [109,] " 1.510370e-14" "3.835891" "1.000" "0.520" " 5.065478e-10" "10"   
## [110,] " 2.953189e-13" "2.547447" "1.000" "0.646" " 9.904404e-09" "10"   
## [111,] "3.528310e-157" "2.182565" "0.923" "0.005" "1.183325e-152" "11"   
## [112,] "1.124497e-149" "1.528145" "0.923" "0.006" "3.771338e-145" "11"   
## [113,] "1.194096e-132" "2.276899" "0.846" "0.006" "4.004759e-128" "11"   
## [114,] " 4.843226e-88" "1.969147" "1.000" "0.023" " 1.624321e-83" "11"   
## [115,] " 6.342572e-46" "1.954123" "1.000" "0.056" " 2.127172e-41" "11"   
## [116,] " 1.077809e-24" "1.833355" "1.000" "0.130" " 3.614755e-20" "11"   
## [117,] " 1.717758e-15" "1.884843" "0.846" "0.127" " 5.761015e-11" "11"   
## [118,] " 7.243264e-12" "1.603618" "1.000" "0.341" " 2.429246e-07" "11"   
## [119,] " 5.239166e-11" "1.499413" "0.615" "0.104" " 1.757112e-06" "11"   
## [120,] " 8.042425e-10" "1.536496" "0.923" "0.298" " 2.697268e-05" "11"   
##        gene        
##   [1,] "C1QC"      
##   [2,] "C1QA"      
##   [3,] "C1QB"      
##   [4,] "HLA-DRB1"  
##   [5,] "FCER1G"    
##   [6,] "CD14"      
##   [7,] "SRGN"      
##   [8,] "CD74"      
##   [9,] "HLA-DRA"   
##  [10,] "LAPTM5"    
##  [11,] "PMAIP1"    
##  [12,] "TNFAIP6"   
##  [13,] "LRP1B"     
##  [14,] "BIRC3"     
##  [15,] "NAV2"      
##  [16,] "PLK2"      
##  [17,] "TTC28"     
##  [18,] "ACSL3"     
##  [19,] "PPP1R15A"  
##  [20,] "EGFR"      
##  [21,] "HIST1H4E"  
##  [22,] "CNTNAP2"   
##  [23,] "HIST1H4H"  
##  [24,] "PCDH11X"   
##  [25,] "ADAMTSL1"  
##  [26,] "DLGAP1"    
##  [27,] "KCNQ5"     
##  [28,] "DMD"       
##  [29,] "IFNB1"     
##  [30,] "COPG2"     
##  [31,] "ELDR"      
##  [32,] "DTX3"      
##  [33,] "CADPS"     
##  [34,] "KIF5A"     
##  [35,] "AC084033.3"
##  [36,] "CDK4"      
##  [37,] "MARS"      
##  [38,] "DCTN2"     
##  [39,] "TSPAN31"   
##  [40,] "DDIT3"     
##  [41,] "IGFBP3"    
##  [42,] "MSMO1"     
##  [43,] "HOPX"      
##  [44,] "CHI3L1"    
##  [45,] "ATP1B2"    
##  [46,] "GATM"      
##  [47,] "RCAN1"     
##  [48,] "PTPRZ1"    
##  [49,] "SERPINE1"  
##  [50,] "AGT"       
##  [51,] "PLXDC2"    
##  [52,] "LRMDA"     
##  [53,] "FMN1"      
##  [54,] "AC074327.1"
##  [55,] "EPB41L3"   
##  [56,] "DOCK4"     
##  [57,] "DAPK1"     
##  [58,] "SCHLAP1"   
##  [59,] "ASCC2"     
##  [60,] "GFRA2"     
##  [61,] "NTNG1"     
##  [62,] "ID1"       
##  [63,] "GPC5"      
##  [64,] "FAM155A"   
##  [65,] "MGST1"     
##  [66,] "METTL7B"   
##  [67,] "CTNNA2"    
##  [68,] "SEC61G"    
##  [69,] "S100A16"   
##  [70,] "ANXA1"     
##  [71,] "BIRC5"     
##  [72,] "UBE2C"     
##  [73,] "TOP2A"     
##  [74,] "TPX2"      
##  [75,] "CENPF"     
##  [76,] "NUSAP1"    
##  [77,] "CCNB1"     
##  [78,] "PTTG1"     
##  [79,] "CKS2"      
##  [80,] "KPNA2"     
##  [81,] "CTGF"      
##  [82,] "ACAT2"     
##  [83,] "NTRK2"     
##  [84,] "FDFT1"     
##  [85,] "DGKB"      
##  [86,] "GAP43"     
##  [87,] "PTN"       
##  [88,] "TUBA1A"    
##  [89,] "GAL"       
##  [90,] "FABP7"     
##  [91,] "PLP1"      
##  [92,] "BCAS1"     
##  [93,] "TF"        
##  [94,] "SLAIN1"    
##  [95,] "CYB5R2"    
##  [96,] "AKAP6"     
##  [97,] "CRYAB"     
##  [98,] "CA2"       
##  [99,] "S100B"     
## [100,] "GLUL"      
## [101,] "COL3A1"    
## [102,] "DCN"       
## [103,] "NDUFA4L2"  
## [104,] "COL1A2"    
## [105,] "COL1A1"    
## [106,] "STC1"      
## [107,] "COL4A1"    
## [108,] "FSTL1"     
## [109,] "FN1"       
## [110,] "SPARC"     
## [111,] "CD2"       
## [112,] "TRBC2"     
## [113,] "GZMA"      
## [114,] "CD52"      
## [115,] "TRAC"      
## [116,] "CD96"      
## [117,] "CCL4"      
## [118,] "PTPRC"     
## [119,] "TC2N"      
## [120,] "PCED1B"

Vizualize a priori chosen markers of tumour subtypes:

markers = list(c('DDIT3', 'ENO2', 'VIM', 'ADM', 'LDHA', 'HILPDA'), c('VIM', 'ANXA1', 'ANXA2', 'CHI3L1', 'CD44'), c('CST3', 'GFAP', 'S100B', 'HOPX', 'SLC1A3', 'MLC1'),
               c('PLP1', 'ALCAM', 'OLIG1', 'OMG', 'PLLP'), c('SOX4', 'DCX', 'CD24', 'DLL3', 'SOX11'), c('RND3', 'SOX11', 'DCX', 'CD24', 'STMN4', 'STMN2', 'DLX5', 'DLX6-AS1'))
names(markers) = c('MES-like2', 'MES-like1', 'AC-like', 'OPC-like', 'NPC-like1', 'NPC-like2')
i = 1
Glioblastoma.list[[i]]$MESlike2 = colSums(Glioblastoma.list[[i]]@assays$RNA@data[markers[[1]],])
Glioblastoma.list[[i]]$MESlike1 = colSums(Glioblastoma.list[[i]]@assays$RNA@data[markers[[2]],])
Glioblastoma.list[[i]]$AClike = colSums(Glioblastoma.list[[i]]@assays$RNA@data[markers[[3]],])
Glioblastoma.list[[i]]$OPClike = colSums(Glioblastoma.list[[i]]@assays$RNA@data[markers[[4]],])
Glioblastoma.list[[i]]$NPClike1 = colSums(Glioblastoma.list[[i]]@assays$RNA@data[markers[[5]],])
Glioblastoma.list[[i]]$NPClike2 = colSums(Glioblastoma.list[[i]]@assays$RNA@data[markers[[6]],])
FeaturePlot(Glioblastoma.list[[i]], features = c('MESlike2', 'MESlike1', 'AClike', 'OPClike', 'NPClike1', 'NPClike2'))

i = 2
Glioblastoma.list[[i]]$MESlike2 = colSums(Glioblastoma.list[[i]]@assays$RNA@data[markers[[1]],])
Glioblastoma.list[[i]]$MESlike1 = colSums(Glioblastoma.list[[i]]@assays$RNA@data[markers[[2]],])
Glioblastoma.list[[i]]$AClike = colSums(Glioblastoma.list[[i]]@assays$RNA@data[markers[[3]],])
Glioblastoma.list[[i]]$OPClike = colSums(Glioblastoma.list[[i]]@assays$RNA@data[markers[[4]],])
Glioblastoma.list[[i]]$NPClike1 = colSums(Glioblastoma.list[[i]]@assays$RNA@data[markers[[5]],])
Glioblastoma.list[[i]]$NPClike2 = colSums(Glioblastoma.list[[i]]@assays$RNA@data[markers[[6]],])
FeaturePlot(Glioblastoma.list[[i]], features = c('MESlike2', 'MESlike1', 'AClike', 'OPClike', 'NPClike1', 'NPClike2'))

Vizualize donor:

i = 1
DimPlot(Glioblastoma.list[[i]], reduction = "umap", group.by = 'Patient')

i = 2
DimPlot(Glioblastoma.list[[i]], reduction = "umap", group.by = 'Patient')

Visualize markers and annotate clusters:

i = 1
#Glioblastoma.0.markers <- FindAllMarkers(Glioblastoma.list[[i]], only.pos = TRUE, min.pct = 0.25, logfc.threshold = 0.25)
#saveRDS(Glioblastoma.0.markers, file = "../data/ZikaGlioblastomas/Glioblastoma.0.markers.rds")
Glioblastoma.0.markers = readRDS("../data/ZikaGlioblastomas/Glioblastoma.0.markers.rds")
top = Glioblastoma.0.markers %>% group_by(cluster) %>% top_n(n = 1, wt = avg_logFC)
FeaturePlot(Glioblastoma.list[[i]], features = top$gene)

top10 <- Glioblastoma.0.markers %>% group_by(cluster) %>% top_n(n = 10, wt = avg_logFC)
DoHeatmap(Glioblastoma.list[[i]], features = top10$gene, cells = 1:dim(Glioblastoma.list[[i]])[2] + NoLegend())

as.matrix(top10)  
##        p_val           avg_logFC  pct.1   pct.2   p_val_adj       cluster
##   [1,] "2.798759e-128" "2.522756" "0.989" "0.223" "9.386477e-124" "0"    
##   [2,] "3.527754e-128" "2.129951" "0.983" "0.205" "1.183138e-123" "0"    
##   [3,] "2.478211e-124" "2.329936" "0.989" "0.225" "8.311422e-120" "0"    
##   [4,] "1.318814e-118" "2.133787" "0.994" "0.250" "4.423038e-114" "0"    
##   [5,] "3.134785e-115" "2.228971" "1.000" "0.291" "1.051344e-110" "0"    
##   [6,] "1.355377e-114" "2.567080" "0.989" "0.282" "4.545664e-110" "0"    
##   [7,] "5.912241e-114" "2.169436" "1.000" "0.295" "1.982847e-109" "0"    
##   [8,] "8.787250e-112" "2.700498" "1.000" "0.311" "2.947068e-107" "0"    
##   [9,] "2.518811e-111" "2.143144" "0.994" "0.262" "8.447589e-107" "0"    
##  [10,] "3.723965e-104" "2.103426" "1.000" "0.395" " 1.248943e-99" "0"    
##  [11,] " 5.390725e-81" "2.038185" "0.953" "0.331" " 1.807941e-76" "1"    
##  [12,] " 3.096750e-73" "1.818058" "0.935" "0.381" " 1.038588e-68" "1"    
##  [13,] " 2.787820e-66" "1.946037" "1.000" "0.759" " 9.349790e-62" "1"    
##  [14,] " 3.809341e-66" "1.423535" "0.923" "0.395" " 1.277577e-61" "1"    
##  [15,] " 3.939624e-62" "1.408315" "0.994" "0.745" " 1.321271e-57" "1"    
##  [16,] " 2.026466e-57" "1.497978" "0.905" "0.420" " 6.796361e-53" "1"    
##  [17,] " 6.328998e-57" "1.633480" "0.970" "0.755" " 2.122619e-52" "1"    
##  [18,] " 1.866497e-56" "1.511335" "0.988" "0.830" " 6.259857e-52" "1"    
##  [19,] " 4.110477e-53" "1.550033" "0.923" "0.597" " 1.378572e-48" "1"    
##  [20,] " 1.494263e-51" "1.516664" "0.982" "0.624" " 5.011461e-47" "1"    
##  [21,] " 7.497445e-78" "1.826130" "0.721" "0.121" " 2.514493e-73" "2"    
##  [22,] " 1.846264e-74" "2.391872" "0.994" "0.897" " 6.192000e-70" "2"    
##  [23,] " 5.179022e-72" "1.623937" "0.864" "0.240" " 1.736940e-67" "2"    
##  [24,] " 2.527806e-60" "1.413136" "0.974" "0.812" " 8.477756e-56" "2"    
##  [25,] " 5.903210e-60" "1.469367" "0.935" "0.507" " 1.979819e-55" "2"    
##  [26,] " 5.530687e-59" "1.790494" "1.000" "0.927" " 1.854882e-54" "2"    
##  [27,] " 3.788774e-57" "1.937084" "0.981" "0.700" " 1.270679e-52" "2"    
##  [28,] " 1.882958e-56" "1.495411" "1.000" "0.996" " 6.315065e-52" "2"    
##  [29,] " 2.766177e-51" "1.440902" "0.714" "0.177" " 9.277206e-47" "2"    
##  [30,] " 1.948553e-47" "1.448895" "0.948" "0.670" " 6.535057e-43" "2"    
##  [31,] "2.696909e-170" "1.536410" "0.930" "0.051" "9.044894e-166" "3"    
##  [32,] " 1.813295e-97" "1.715417" "0.937" "0.228" " 6.081429e-93" "3"    
##  [33,] " 8.325655e-88" "1.961581" "0.965" "0.282" " 2.792258e-83" "3"    
##  [34,] " 2.807664e-79" "1.836803" "0.986" "0.546" " 9.416344e-75" "3"    
##  [35,] " 4.265136e-76" "1.904044" "0.986" "0.601" " 1.430441e-71" "3"    
##  [36,] " 4.129375e-75" "1.849851" "0.993" "0.638" " 1.384910e-70" "3"    
##  [37,] " 9.078462e-75" "2.576137" "0.986" "0.773" " 3.044735e-70" "3"    
##  [38,] " 9.823225e-75" "2.063922" "0.986" "0.614" " 3.294513e-70" "3"    
##  [39,] " 6.953299e-73" "1.886080" "0.972" "0.537" " 2.331997e-68" "3"    
##  [40,] " 2.234984e-68" "2.417912" "0.986" "0.758" " 7.495690e-64" "3"    
##  [41,] " 1.167120e-54" "2.252501" "0.790" "0.206" " 3.914288e-50" "4"    
##  [42,] " 4.401099e-52" "1.387220" "0.975" "0.512" " 1.476040e-47" "4"    
##  [43,] " 2.148337e-45" "1.450118" "0.840" "0.307" " 7.205092e-41" "4"    
##  [44,] " 2.076797e-42" "2.257484" "0.933" "0.476" " 6.965162e-38" "4"    
##  [45,] " 1.702096e-41" "1.615830" "0.874" "0.416" " 5.708489e-37" "4"    
##  [46,] " 2.759173e-41" "1.452258" "0.916" "0.527" " 9.253714e-37" "4"    
##  [47,] " 1.176994e-39" "1.446625" "0.975" "0.628" " 3.947404e-35" "4"    
##  [48,] " 2.298906e-34" "1.633594" "1.000" "0.975" " 7.710072e-30" "4"    
##  [49,] " 2.241069e-21" "1.797888" "0.773" "0.444" " 7.516096e-17" "4"    
##  [50,] " 1.221268e-18" "1.444292" "0.672" "0.342" " 4.095887e-14" "4"    
##  [51,] " 7.918077e-48" "1.622165" "0.990" "0.431" " 2.655565e-43" "5"    
##  [52,] " 2.238636e-46" "1.696176" "1.000" "0.722" " 7.507939e-42" "5"    
##  [53,] " 2.860564e-43" "1.459257" "0.929" "0.404" " 9.593760e-39" "5"    
##  [54,] " 4.813143e-41" "1.435189" "0.848" "0.277" " 1.614232e-36" "5"    
##  [55,] " 3.354506e-40" "1.458001" "0.909" "0.391" " 1.125034e-35" "5"    
##  [56,] " 5.105091e-40" "1.447743" "1.000" "0.790" " 1.712145e-35" "5"    
##  [57,] " 1.080295e-23" "1.418654" "0.899" "0.719" " 3.623092e-19" "5"    
##  [58,] " 1.197681e-20" "1.753500" "1.000" "0.996" " 4.016783e-16" "5"    
##  [59,] " 1.312912e-11" "1.967047" "0.980" "0.955" " 4.403245e-07" "5"    
##  [60,] " 1.819123e-06" "1.646971" "0.545" "0.420" " 6.100973e-02" "5"    
##  [61,] " 1.947917e-52" "1.186712" "0.922" "0.288" " 6.532923e-48" "6"    
##  [62,] " 2.604675e-46" "1.484916" "0.956" "0.408" " 8.735558e-42" "6"    
##  [63,] " 5.102311e-43" "1.315888" "0.933" "0.437" " 1.711213e-38" "6"    
##  [64,] " 1.494108e-42" "1.580178" "0.833" "0.266" " 5.010940e-38" "6"    
##  [65,] " 1.421163e-39" "1.139706" "0.889" "0.391" " 4.766297e-35" "6"    
##  [66,] " 7.483431e-39" "1.488748" "0.800" "0.228" " 2.509793e-34" "6"    
##  [67,] " 3.977564e-38" "1.387418" "0.989" "0.712" " 1.333995e-33" "6"    
##  [68,] " 1.357131e-32" "1.878086" "1.000" "0.931" " 4.551547e-28" "6"    
##  [69,] " 1.628702e-28" "1.268166" "0.900" "0.584" " 5.462342e-24" "6"    
##  [70,] " 3.900800e-26" "1.294382" "0.956" "0.689" " 1.308250e-21" "6"    
##  [71,] " 8.572137e-90" "1.768726" "1.000" "0.130" " 2.874923e-85" "7"    
##  [72,] " 1.368958e-87" "2.042924" "0.985" "0.129" " 4.591212e-83" "7"    
##  [73,] " 5.452865e-87" "2.236550" "0.985" "0.129" " 1.828782e-82" "7"    
##  [74,] " 3.346281e-64" "1.856521" "0.985" "0.221" " 1.122276e-59" "7"    
##  [75,] " 6.084572e-58" "1.687365" "0.970" "0.235" " 2.040644e-53" "7"    
##  [76,] " 9.481351e-58" "2.451641" "1.000" "0.285" " 3.179856e-53" "7"    
##  [77,] " 4.857875e-55" "2.280891" "0.924" "0.205" " 1.629234e-50" "7"    
##  [78,] " 2.406805e-41" "1.880665" "1.000" "0.538" " 8.071942e-37" "7"    
##  [79,] " 4.244582e-41" "1.753201" "1.000" "0.505" " 1.423548e-36" "7"    
##  [80,] " 4.642748e-36" "1.927642" "1.000" "0.633" " 1.557085e-31" "7"    
##  [81,] " 1.119942e-30" "1.613989" "0.723" "0.184" " 3.756061e-26" "8"    
##  [82,] " 2.331677e-29" "1.476633" "0.985" "0.648" " 7.819977e-25" "8"    
##  [83,] " 3.164093e-29" "1.066209" "0.954" "0.427" " 1.061174e-24" "8"    
##  [84,] " 4.007181e-29" "1.297525" "0.985" "0.649" " 1.343928e-24" "8"    
##  [85,] " 1.213273e-28" "1.408490" "0.985" "0.666" " 4.069074e-24" "8"    
##  [86,] " 1.192655e-25" "1.062717" "1.000" "0.855" " 3.999926e-21" "8"    
##  [87,] " 3.896175e-25" "1.414331" "1.000" "0.788" " 1.306699e-20" "8"    
##  [88,] " 8.366594e-24" "1.160669" "1.000" "0.912" " 2.805988e-19" "8"    
##  [89,] " 2.247137e-22" "1.263117" "0.846" "0.299" " 7.536448e-18" "8"    
##  [90,] " 2.352472e-17" "1.046039" "0.954" "0.643" " 7.889721e-13" "8"    
##  [91,] " 1.735046e-63" "3.263369" "0.917" "0.118" " 5.818996e-59" "9"    
##  [92,] " 2.762613e-55" "2.569412" "0.979" "0.189" " 9.265251e-51" "9"    
##  [93,] " 6.419675e-44" "2.227550" "0.771" "0.120" " 2.153031e-39" "9"    
##  [94,] " 6.937651e-42" "2.623658" "0.958" "0.267" " 2.326749e-37" "9"    
##  [95,] " 2.289617e-38" "2.592318" "0.938" "0.279" " 7.678916e-34" "9"    
##  [96,] " 8.660222e-32" "3.175171" "1.000" "0.752" " 2.904465e-27" "9"    
##  [97,] " 6.690497e-26" "2.182278" "1.000" "0.664" " 2.243859e-21" "9"    
##  [98,] " 2.150475e-19" "2.240637" "0.875" "0.457" " 7.212262e-15" "9"    
##  [99,] " 3.674938e-19" "2.320411" "0.958" "0.618" " 1.232501e-14" "9"    
## [100,] " 7.397930e-19" "2.200289" "0.958" "0.921" " 2.481118e-14" "9"    
## [101,] "1.551403e-165" "2.860848" "1.000" "0.009" "5.203095e-161" "10"   
## [102,] " 9.468058e-83" "3.255233" "1.000" "0.035" " 3.175397e-78" "10"   
## [103,] " 1.487256e-55" "3.158075" "1.000" "0.063" " 4.987960e-51" "10"   
## [104,] " 5.362388e-38" "3.206616" "1.000" "0.107" " 1.798438e-33" "10"   
## [105,] " 1.073640e-34" "2.909807" "0.833" "0.074" " 3.600772e-30" "10"   
## [106,] " 3.716395e-31" "2.749332" "0.667" "0.049" " 1.246404e-26" "10"   
## [107,] " 3.859706e-17" "2.549649" "1.000" "0.351" " 1.294468e-12" "10"   
## [108,] " 1.293738e-16" "2.597582" "1.000" "0.334" " 4.338939e-12" "10"   
## [109,] " 1.510370e-14" "3.835891" "1.000" "0.520" " 5.065478e-10" "10"   
## [110,] " 2.953189e-13" "2.547447" "1.000" "0.646" " 9.904404e-09" "10"   
## [111,] "3.528310e-157" "2.182565" "0.923" "0.005" "1.183325e-152" "11"   
## [112,] "1.124497e-149" "1.528145" "0.923" "0.006" "3.771338e-145" "11"   
## [113,] "1.194096e-132" "2.276899" "0.846" "0.006" "4.004759e-128" "11"   
## [114,] " 4.843226e-88" "1.969147" "1.000" "0.023" " 1.624321e-83" "11"   
## [115,] " 6.342572e-46" "1.954123" "1.000" "0.056" " 2.127172e-41" "11"   
## [116,] " 1.077809e-24" "1.833355" "1.000" "0.130" " 3.614755e-20" "11"   
## [117,] " 1.717758e-15" "1.884843" "0.846" "0.127" " 5.761015e-11" "11"   
## [118,] " 7.243264e-12" "1.603618" "1.000" "0.341" " 2.429246e-07" "11"   
## [119,] " 5.239166e-11" "1.499413" "0.615" "0.104" " 1.757112e-06" "11"   
## [120,] " 8.042425e-10" "1.536496" "0.923" "0.298" " 2.697268e-05" "11"   
##        gene        
##   [1,] "C1QC"      
##   [2,] "C1QA"      
##   [3,] "C1QB"      
##   [4,] "HLA-DRB1"  
##   [5,] "FCER1G"    
##   [6,] "CD14"      
##   [7,] "SRGN"      
##   [8,] "CD74"      
##   [9,] "HLA-DRA"   
##  [10,] "LAPTM5"    
##  [11,] "PMAIP1"    
##  [12,] "TNFAIP6"   
##  [13,] "LRP1B"     
##  [14,] "BIRC3"     
##  [15,] "NAV2"      
##  [16,] "PLK2"      
##  [17,] "TTC28"     
##  [18,] "ACSL3"     
##  [19,] "PPP1R15A"  
##  [20,] "EGFR"      
##  [21,] "HIST1H4E"  
##  [22,] "CNTNAP2"   
##  [23,] "HIST1H4H"  
##  [24,] "PCDH11X"   
##  [25,] "ADAMTSL1"  
##  [26,] "DLGAP1"    
##  [27,] "KCNQ5"     
##  [28,] "DMD"       
##  [29,] "IFNB1"     
##  [30,] "COPG2"     
##  [31,] "ELDR"      
##  [32,] "DTX3"      
##  [33,] "CADPS"     
##  [34,] "KIF5A"     
##  [35,] "AC084033.3"
##  [36,] "CDK4"      
##  [37,] "MARS"      
##  [38,] "DCTN2"     
##  [39,] "TSPAN31"   
##  [40,] "DDIT3"     
##  [41,] "IGFBP3"    
##  [42,] "MSMO1"     
##  [43,] "HOPX"      
##  [44,] "CHI3L1"    
##  [45,] "ATP1B2"    
##  [46,] "GATM"      
##  [47,] "RCAN1"     
##  [48,] "PTPRZ1"    
##  [49,] "SERPINE1"  
##  [50,] "AGT"       
##  [51,] "PLXDC2"    
##  [52,] "LRMDA"     
##  [53,] "FMN1"      
##  [54,] "AC074327.1"
##  [55,] "EPB41L3"   
##  [56,] "DOCK4"     
##  [57,] "DAPK1"     
##  [58,] "SCHLAP1"   
##  [59,] "ASCC2"     
##  [60,] "GFRA2"     
##  [61,] "NTNG1"     
##  [62,] "ID1"       
##  [63,] "GPC5"      
##  [64,] "FAM155A"   
##  [65,] "MGST1"     
##  [66,] "METTL7B"   
##  [67,] "CTNNA2"    
##  [68,] "SEC61G"    
##  [69,] "S100A16"   
##  [70,] "ANXA1"     
##  [71,] "BIRC5"     
##  [72,] "UBE2C"     
##  [73,] "TOP2A"     
##  [74,] "TPX2"      
##  [75,] "CENPF"     
##  [76,] "NUSAP1"    
##  [77,] "CCNB1"     
##  [78,] "PTTG1"     
##  [79,] "CKS2"      
##  [80,] "KPNA2"     
##  [81,] "CTGF"      
##  [82,] "ACAT2"     
##  [83,] "NTRK2"     
##  [84,] "FDFT1"     
##  [85,] "DGKB"      
##  [86,] "GAP43"     
##  [87,] "PTN"       
##  [88,] "TUBA1A"    
##  [89,] "GAL"       
##  [90,] "FABP7"     
##  [91,] "PLP1"      
##  [92,] "BCAS1"     
##  [93,] "TF"        
##  [94,] "SLAIN1"    
##  [95,] "CYB5R2"    
##  [96,] "AKAP6"     
##  [97,] "CRYAB"     
##  [98,] "CA2"       
##  [99,] "S100B"     
## [100,] "GLUL"      
## [101,] "COL3A1"    
## [102,] "DCN"       
## [103,] "NDUFA4L2"  
## [104,] "COL1A2"    
## [105,] "COL1A1"    
## [106,] "STC1"      
## [107,] "COL4A1"    
## [108,] "FSTL1"     
## [109,] "FN1"       
## [110,] "SPARC"     
## [111,] "CD2"       
## [112,] "TRBC2"     
## [113,] "GZMA"      
## [114,] "CD52"      
## [115,] "TRAC"      
## [116,] "CD96"      
## [117,] "CCL4"      
## [118,] "PTPRC"     
## [119,] "TC2N"      
## [120,] "PCED1B"
i = 2
#Glioblastoma.1.markers <- FindAllMarkers(Glioblastoma.list[[i]], only.pos = TRUE, min.pct = 0.25, logfc.threshold = 0.25)
#saveRDS(Glioblastoma.1.markers, file = "../data/ZikaGlioblastomas/Glioblastoma.1.markers.rds")
Glioblastoma.1.markers = readRDS("../data/ZikaGlioblastomas/Glioblastoma.1.markers.rds")
top = Glioblastoma.1.markers %>% group_by(cluster) %>% top_n(n = 1, wt = avg_logFC)
FeaturePlot(Glioblastoma.list[[i]], features = top$gene)

top5 <- Glioblastoma.1.markers %>% group_by(cluster) %>% top_n(n = 5, wt = avg_logFC)
DoHeatmap(Glioblastoma.list[[i]], features = top5$gene, cells = sample(1:dim(Glioblastoma.list[[i]])[2], 1000))

as.matrix(top10)
##        p_val           avg_logFC  pct.1   pct.2   p_val_adj       cluster
##   [1,] "2.798759e-128" "2.522756" "0.989" "0.223" "9.386477e-124" "0"    
##   [2,] "3.527754e-128" "2.129951" "0.983" "0.205" "1.183138e-123" "0"    
##   [3,] "2.478211e-124" "2.329936" "0.989" "0.225" "8.311422e-120" "0"    
##   [4,] "1.318814e-118" "2.133787" "0.994" "0.250" "4.423038e-114" "0"    
##   [5,] "3.134785e-115" "2.228971" "1.000" "0.291" "1.051344e-110" "0"    
##   [6,] "1.355377e-114" "2.567080" "0.989" "0.282" "4.545664e-110" "0"    
##   [7,] "5.912241e-114" "2.169436" "1.000" "0.295" "1.982847e-109" "0"    
##   [8,] "8.787250e-112" "2.700498" "1.000" "0.311" "2.947068e-107" "0"    
##   [9,] "2.518811e-111" "2.143144" "0.994" "0.262" "8.447589e-107" "0"    
##  [10,] "3.723965e-104" "2.103426" "1.000" "0.395" " 1.248943e-99" "0"    
##  [11,] " 5.390725e-81" "2.038185" "0.953" "0.331" " 1.807941e-76" "1"    
##  [12,] " 3.096750e-73" "1.818058" "0.935" "0.381" " 1.038588e-68" "1"    
##  [13,] " 2.787820e-66" "1.946037" "1.000" "0.759" " 9.349790e-62" "1"    
##  [14,] " 3.809341e-66" "1.423535" "0.923" "0.395" " 1.277577e-61" "1"    
##  [15,] " 3.939624e-62" "1.408315" "0.994" "0.745" " 1.321271e-57" "1"    
##  [16,] " 2.026466e-57" "1.497978" "0.905" "0.420" " 6.796361e-53" "1"    
##  [17,] " 6.328998e-57" "1.633480" "0.970" "0.755" " 2.122619e-52" "1"    
##  [18,] " 1.866497e-56" "1.511335" "0.988" "0.830" " 6.259857e-52" "1"    
##  [19,] " 4.110477e-53" "1.550033" "0.923" "0.597" " 1.378572e-48" "1"    
##  [20,] " 1.494263e-51" "1.516664" "0.982" "0.624" " 5.011461e-47" "1"    
##  [21,] " 7.497445e-78" "1.826130" "0.721" "0.121" " 2.514493e-73" "2"    
##  [22,] " 1.846264e-74" "2.391872" "0.994" "0.897" " 6.192000e-70" "2"    
##  [23,] " 5.179022e-72" "1.623937" "0.864" "0.240" " 1.736940e-67" "2"    
##  [24,] " 2.527806e-60" "1.413136" "0.974" "0.812" " 8.477756e-56" "2"    
##  [25,] " 5.903210e-60" "1.469367" "0.935" "0.507" " 1.979819e-55" "2"    
##  [26,] " 5.530687e-59" "1.790494" "1.000" "0.927" " 1.854882e-54" "2"    
##  [27,] " 3.788774e-57" "1.937084" "0.981" "0.700" " 1.270679e-52" "2"    
##  [28,] " 1.882958e-56" "1.495411" "1.000" "0.996" " 6.315065e-52" "2"    
##  [29,] " 2.766177e-51" "1.440902" "0.714" "0.177" " 9.277206e-47" "2"    
##  [30,] " 1.948553e-47" "1.448895" "0.948" "0.670" " 6.535057e-43" "2"    
##  [31,] "2.696909e-170" "1.536410" "0.930" "0.051" "9.044894e-166" "3"    
##  [32,] " 1.813295e-97" "1.715417" "0.937" "0.228" " 6.081429e-93" "3"    
##  [33,] " 8.325655e-88" "1.961581" "0.965" "0.282" " 2.792258e-83" "3"    
##  [34,] " 2.807664e-79" "1.836803" "0.986" "0.546" " 9.416344e-75" "3"    
##  [35,] " 4.265136e-76" "1.904044" "0.986" "0.601" " 1.430441e-71" "3"    
##  [36,] " 4.129375e-75" "1.849851" "0.993" "0.638" " 1.384910e-70" "3"    
##  [37,] " 9.078462e-75" "2.576137" "0.986" "0.773" " 3.044735e-70" "3"    
##  [38,] " 9.823225e-75" "2.063922" "0.986" "0.614" " 3.294513e-70" "3"    
##  [39,] " 6.953299e-73" "1.886080" "0.972" "0.537" " 2.331997e-68" "3"    
##  [40,] " 2.234984e-68" "2.417912" "0.986" "0.758" " 7.495690e-64" "3"    
##  [41,] " 1.167120e-54" "2.252501" "0.790" "0.206" " 3.914288e-50" "4"    
##  [42,] " 4.401099e-52" "1.387220" "0.975" "0.512" " 1.476040e-47" "4"    
##  [43,] " 2.148337e-45" "1.450118" "0.840" "0.307" " 7.205092e-41" "4"    
##  [44,] " 2.076797e-42" "2.257484" "0.933" "0.476" " 6.965162e-38" "4"    
##  [45,] " 1.702096e-41" "1.615830" "0.874" "0.416" " 5.708489e-37" "4"    
##  [46,] " 2.759173e-41" "1.452258" "0.916" "0.527" " 9.253714e-37" "4"    
##  [47,] " 1.176994e-39" "1.446625" "0.975" "0.628" " 3.947404e-35" "4"    
##  [48,] " 2.298906e-34" "1.633594" "1.000" "0.975" " 7.710072e-30" "4"    
##  [49,] " 2.241069e-21" "1.797888" "0.773" "0.444" " 7.516096e-17" "4"    
##  [50,] " 1.221268e-18" "1.444292" "0.672" "0.342" " 4.095887e-14" "4"    
##  [51,] " 7.918077e-48" "1.622165" "0.990" "0.431" " 2.655565e-43" "5"    
##  [52,] " 2.238636e-46" "1.696176" "1.000" "0.722" " 7.507939e-42" "5"    
##  [53,] " 2.860564e-43" "1.459257" "0.929" "0.404" " 9.593760e-39" "5"    
##  [54,] " 4.813143e-41" "1.435189" "0.848" "0.277" " 1.614232e-36" "5"    
##  [55,] " 3.354506e-40" "1.458001" "0.909" "0.391" " 1.125034e-35" "5"    
##  [56,] " 5.105091e-40" "1.447743" "1.000" "0.790" " 1.712145e-35" "5"    
##  [57,] " 1.080295e-23" "1.418654" "0.899" "0.719" " 3.623092e-19" "5"    
##  [58,] " 1.197681e-20" "1.753500" "1.000" "0.996" " 4.016783e-16" "5"    
##  [59,] " 1.312912e-11" "1.967047" "0.980" "0.955" " 4.403245e-07" "5"    
##  [60,] " 1.819123e-06" "1.646971" "0.545" "0.420" " 6.100973e-02" "5"    
##  [61,] " 1.947917e-52" "1.186712" "0.922" "0.288" " 6.532923e-48" "6"    
##  [62,] " 2.604675e-46" "1.484916" "0.956" "0.408" " 8.735558e-42" "6"    
##  [63,] " 5.102311e-43" "1.315888" "0.933" "0.437" " 1.711213e-38" "6"    
##  [64,] " 1.494108e-42" "1.580178" "0.833" "0.266" " 5.010940e-38" "6"    
##  [65,] " 1.421163e-39" "1.139706" "0.889" "0.391" " 4.766297e-35" "6"    
##  [66,] " 7.483431e-39" "1.488748" "0.800" "0.228" " 2.509793e-34" "6"    
##  [67,] " 3.977564e-38" "1.387418" "0.989" "0.712" " 1.333995e-33" "6"    
##  [68,] " 1.357131e-32" "1.878086" "1.000" "0.931" " 4.551547e-28" "6"    
##  [69,] " 1.628702e-28" "1.268166" "0.900" "0.584" " 5.462342e-24" "6"    
##  [70,] " 3.900800e-26" "1.294382" "0.956" "0.689" " 1.308250e-21" "6"    
##  [71,] " 8.572137e-90" "1.768726" "1.000" "0.130" " 2.874923e-85" "7"    
##  [72,] " 1.368958e-87" "2.042924" "0.985" "0.129" " 4.591212e-83" "7"    
##  [73,] " 5.452865e-87" "2.236550" "0.985" "0.129" " 1.828782e-82" "7"    
##  [74,] " 3.346281e-64" "1.856521" "0.985" "0.221" " 1.122276e-59" "7"    
##  [75,] " 6.084572e-58" "1.687365" "0.970" "0.235" " 2.040644e-53" "7"    
##  [76,] " 9.481351e-58" "2.451641" "1.000" "0.285" " 3.179856e-53" "7"    
##  [77,] " 4.857875e-55" "2.280891" "0.924" "0.205" " 1.629234e-50" "7"    
##  [78,] " 2.406805e-41" "1.880665" "1.000" "0.538" " 8.071942e-37" "7"    
##  [79,] " 4.244582e-41" "1.753201" "1.000" "0.505" " 1.423548e-36" "7"    
##  [80,] " 4.642748e-36" "1.927642" "1.000" "0.633" " 1.557085e-31" "7"    
##  [81,] " 1.119942e-30" "1.613989" "0.723" "0.184" " 3.756061e-26" "8"    
##  [82,] " 2.331677e-29" "1.476633" "0.985" "0.648" " 7.819977e-25" "8"    
##  [83,] " 3.164093e-29" "1.066209" "0.954" "0.427" " 1.061174e-24" "8"    
##  [84,] " 4.007181e-29" "1.297525" "0.985" "0.649" " 1.343928e-24" "8"    
##  [85,] " 1.213273e-28" "1.408490" "0.985" "0.666" " 4.069074e-24" "8"    
##  [86,] " 1.192655e-25" "1.062717" "1.000" "0.855" " 3.999926e-21" "8"    
##  [87,] " 3.896175e-25" "1.414331" "1.000" "0.788" " 1.306699e-20" "8"    
##  [88,] " 8.366594e-24" "1.160669" "1.000" "0.912" " 2.805988e-19" "8"    
##  [89,] " 2.247137e-22" "1.263117" "0.846" "0.299" " 7.536448e-18" "8"    
##  [90,] " 2.352472e-17" "1.046039" "0.954" "0.643" " 7.889721e-13" "8"    
##  [91,] " 1.735046e-63" "3.263369" "0.917" "0.118" " 5.818996e-59" "9"    
##  [92,] " 2.762613e-55" "2.569412" "0.979" "0.189" " 9.265251e-51" "9"    
##  [93,] " 6.419675e-44" "2.227550" "0.771" "0.120" " 2.153031e-39" "9"    
##  [94,] " 6.937651e-42" "2.623658" "0.958" "0.267" " 2.326749e-37" "9"    
##  [95,] " 2.289617e-38" "2.592318" "0.938" "0.279" " 7.678916e-34" "9"    
##  [96,] " 8.660222e-32" "3.175171" "1.000" "0.752" " 2.904465e-27" "9"    
##  [97,] " 6.690497e-26" "2.182278" "1.000" "0.664" " 2.243859e-21" "9"    
##  [98,] " 2.150475e-19" "2.240637" "0.875" "0.457" " 7.212262e-15" "9"    
##  [99,] " 3.674938e-19" "2.320411" "0.958" "0.618" " 1.232501e-14" "9"    
## [100,] " 7.397930e-19" "2.200289" "0.958" "0.921" " 2.481118e-14" "9"    
## [101,] "1.551403e-165" "2.860848" "1.000" "0.009" "5.203095e-161" "10"   
## [102,] " 9.468058e-83" "3.255233" "1.000" "0.035" " 3.175397e-78" "10"   
## [103,] " 1.487256e-55" "3.158075" "1.000" "0.063" " 4.987960e-51" "10"   
## [104,] " 5.362388e-38" "3.206616" "1.000" "0.107" " 1.798438e-33" "10"   
## [105,] " 1.073640e-34" "2.909807" "0.833" "0.074" " 3.600772e-30" "10"   
## [106,] " 3.716395e-31" "2.749332" "0.667" "0.049" " 1.246404e-26" "10"   
## [107,] " 3.859706e-17" "2.549649" "1.000" "0.351" " 1.294468e-12" "10"   
## [108,] " 1.293738e-16" "2.597582" "1.000" "0.334" " 4.338939e-12" "10"   
## [109,] " 1.510370e-14" "3.835891" "1.000" "0.520" " 5.065478e-10" "10"   
## [110,] " 2.953189e-13" "2.547447" "1.000" "0.646" " 9.904404e-09" "10"   
## [111,] "3.528310e-157" "2.182565" "0.923" "0.005" "1.183325e-152" "11"   
## [112,] "1.124497e-149" "1.528145" "0.923" "0.006" "3.771338e-145" "11"   
## [113,] "1.194096e-132" "2.276899" "0.846" "0.006" "4.004759e-128" "11"   
## [114,] " 4.843226e-88" "1.969147" "1.000" "0.023" " 1.624321e-83" "11"   
## [115,] " 6.342572e-46" "1.954123" "1.000" "0.056" " 2.127172e-41" "11"   
## [116,] " 1.077809e-24" "1.833355" "1.000" "0.130" " 3.614755e-20" "11"   
## [117,] " 1.717758e-15" "1.884843" "0.846" "0.127" " 5.761015e-11" "11"   
## [118,] " 7.243264e-12" "1.603618" "1.000" "0.341" " 2.429246e-07" "11"   
## [119,] " 5.239166e-11" "1.499413" "0.615" "0.104" " 1.757112e-06" "11"   
## [120,] " 8.042425e-10" "1.536496" "0.923" "0.298" " 2.697268e-05" "11"   
##        gene        
##   [1,] "C1QC"      
##   [2,] "C1QA"      
##   [3,] "C1QB"      
##   [4,] "HLA-DRB1"  
##   [5,] "FCER1G"    
##   [6,] "CD14"      
##   [7,] "SRGN"      
##   [8,] "CD74"      
##   [9,] "HLA-DRA"   
##  [10,] "LAPTM5"    
##  [11,] "PMAIP1"    
##  [12,] "TNFAIP6"   
##  [13,] "LRP1B"     
##  [14,] "BIRC3"     
##  [15,] "NAV2"      
##  [16,] "PLK2"      
##  [17,] "TTC28"     
##  [18,] "ACSL3"     
##  [19,] "PPP1R15A"  
##  [20,] "EGFR"      
##  [21,] "HIST1H4E"  
##  [22,] "CNTNAP2"   
##  [23,] "HIST1H4H"  
##  [24,] "PCDH11X"   
##  [25,] "ADAMTSL1"  
##  [26,] "DLGAP1"    
##  [27,] "KCNQ5"     
##  [28,] "DMD"       
##  [29,] "IFNB1"     
##  [30,] "COPG2"     
##  [31,] "ELDR"      
##  [32,] "DTX3"      
##  [33,] "CADPS"     
##  [34,] "KIF5A"     
##  [35,] "AC084033.3"
##  [36,] "CDK4"      
##  [37,] "MARS"      
##  [38,] "DCTN2"     
##  [39,] "TSPAN31"   
##  [40,] "DDIT3"     
##  [41,] "IGFBP3"    
##  [42,] "MSMO1"     
##  [43,] "HOPX"      
##  [44,] "CHI3L1"    
##  [45,] "ATP1B2"    
##  [46,] "GATM"      
##  [47,] "RCAN1"     
##  [48,] "PTPRZ1"    
##  [49,] "SERPINE1"  
##  [50,] "AGT"       
##  [51,] "PLXDC2"    
##  [52,] "LRMDA"     
##  [53,] "FMN1"      
##  [54,] "AC074327.1"
##  [55,] "EPB41L3"   
##  [56,] "DOCK4"     
##  [57,] "DAPK1"     
##  [58,] "SCHLAP1"   
##  [59,] "ASCC2"     
##  [60,] "GFRA2"     
##  [61,] "NTNG1"     
##  [62,] "ID1"       
##  [63,] "GPC5"      
##  [64,] "FAM155A"   
##  [65,] "MGST1"     
##  [66,] "METTL7B"   
##  [67,] "CTNNA2"    
##  [68,] "SEC61G"    
##  [69,] "S100A16"   
##  [70,] "ANXA1"     
##  [71,] "BIRC5"     
##  [72,] "UBE2C"     
##  [73,] "TOP2A"     
##  [74,] "TPX2"      
##  [75,] "CENPF"     
##  [76,] "NUSAP1"    
##  [77,] "CCNB1"     
##  [78,] "PTTG1"     
##  [79,] "CKS2"      
##  [80,] "KPNA2"     
##  [81,] "CTGF"      
##  [82,] "ACAT2"     
##  [83,] "NTRK2"     
##  [84,] "FDFT1"     
##  [85,] "DGKB"      
##  [86,] "GAP43"     
##  [87,] "PTN"       
##  [88,] "TUBA1A"    
##  [89,] "GAL"       
##  [90,] "FABP7"     
##  [91,] "PLP1"      
##  [92,] "BCAS1"     
##  [93,] "TF"        
##  [94,] "SLAIN1"    
##  [95,] "CYB5R2"    
##  [96,] "AKAP6"     
##  [97,] "CRYAB"     
##  [98,] "CA2"       
##  [99,] "S100B"     
## [100,] "GLUL"      
## [101,] "COL3A1"    
## [102,] "DCN"       
## [103,] "NDUFA4L2"  
## [104,] "COL1A2"    
## [105,] "COL1A1"    
## [106,] "STC1"      
## [107,] "COL4A1"    
## [108,] "FSTL1"     
## [109,] "FN1"       
## [110,] "SPARC"     
## [111,] "CD2"       
## [112,] "TRBC2"     
## [113,] "GZMA"      
## [114,] "CD52"      
## [115,] "TRAC"      
## [116,] "CD96"      
## [117,] "CCL4"      
## [118,] "PTPRC"     
## [119,] "TC2N"      
## [120,] "PCED1B"

Vizualize a priori chosen markers of tumour subtypes:

viral_response = c('DDIT3', 'IFNB1')
i = 1
Glioblastoma.list[[i]]$viral_response = colSums(Glioblastoma.list[[i]]@assays$RNA@data[viral_response,])
FeaturePlot(Glioblastoma.list[[i]], features = 'viral_response')

i = 2
Glioblastoma.list[[i]]$viral_response = colSums(Glioblastoma.list[[i]]@assays$RNA@data[viral_response,])
FeaturePlot(Glioblastoma.list[[i]], features = 'viral_response')